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#edge computing Open access

Internet of Things Infrastructure Research Mapping

Aug 2026 · West Science Information System and Technology · Vol 4, pp. 245-257

Abstract

The fast pace of developing the concept of digital transformation made the Internet of Things infrastructure a crucial basis for connected systems, intelligent applications, and sustainable technological ecosystems. The purpose of this study is to conduct a bibliometric analysis and identify the patterns of development, intellectual structure, collaboration, and current research trends in the IoT infrastructure. Scientific publications related to the topic were gathered and analyzed using the software VOSviewer in order to investigate citation performance, co-authorship network, collaborations between institutions and countries, co-occurrence of keywords, thematic dynamics, and patterns of research density. It was found out that there has been a considerable increase in the amount of IoT infrastructure research, with cybersecurity, secure communication, edge computing, fog computing, smart cities, and intelligent infrastructure being identified as leading research topics. Citation analysis suggests that papers dedicated to IoT security framework, intrusion detection system, critical infrastructure protection, and distributed computing architecture have had a significant impact on this field. Collaboration analysis has indicated the presence of strong international research networks with China, India, USA, Germany, and the UK being recognized as the key contributors. Finally, it has been found out that the research has evolved from addressing connectivity challenges to advanced research which includes artificial intelligence, machine learning, privacy protection, energy efficiency, and autonomous IoT systems.

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#computer vision Review Sep 2017

Agile Software Development Methods: Review and Analysis

Agile - denoting "the quality of being agile, readiness for motion, nimbleness, activity, dexterity in motion" - software development methods are attempting to offer an answer to the eager business community asking for lighter weight along with faster and nimbler software development processes. This is especially the case with the rapidly growing and volatile Internet software industry as well as for the emerging mobile application environment. The new agile methods have evoked substantial amount of literature and debates. However, academic research on the subject is still scarce, as most of existing publications are written by practitioners or consultants. The aim of this publication is to begin filling this gap by systematically reviewing the existing literature on agile software development methodologies. This publication has three purposes. First, it proposes a definition and a classification of agile software development approaches. Second, it analyses ten software development methods that can be characterized as being "agile" against the defined criterion. Third, it compares these methods and highlights their similarities and differences. Based on this analysis, future research needs are identified and discussed.

P. Abrahamsson, O. Salo, Jussi Ronkainen et al. · 728 citations · ⚡54
#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

Context: Software startups are newly created companies with no operating history and fast in producing cutting-edge technologies. These companies develop software under highly uncertain conditions, tackling fast-growing markets under severe lack of resources. Therefore, software startups present a unique combination of characteristics which pose several challenges to software development activities. Objective: This study aims to structure and analyze the literature on software development in startup companies, determining thereby the potential for technology transfer and identifying software development work practices reported by practitioners and researchers. Method: We conducted a systematic mapping study, developing a classification schema, ranking the selected primary studies according their rigor and relevance, and analyzing reported software development work practices in startups. Results: A total of 43 primary studies were identified and mapped, synthesizing the available evidence on software development in startups. Only 16 studies are entirely dedicated to software development in startups, of which 10 result in a weak contribution (advice and implications (6); lesson learned (3); tool (1)). Nineteen studies focus on managerial and organizational factors. Moreover, only 9 studies exhibit high scientific rigor and relevance. From the reviewed primary studies, 213 software engineering work practices were extracted, categorized and analyzed. Conclusion: This mapping study provides the first systematic exploration of the state-of-art on software startup research. The existing body of knowledge is limited to a few high quality studies. Furthermore, the results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54

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